Simultaneous nested modeling from the synoptic scale to the LES scale for wind energy applications

Liu, Yubao; Warner, Thomas T.; Liu, Yue-Wei; Vincent, Claire Louise; Wu, Wanli; Mahoney, Bill; Swerdlin, Scott; Parks, Keith; Boehnert, Jennifer

doi:10.1016/j.jweia.2011.01.013

Cited by 87 publications

(57 citation statements)

References 15 publications

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“…Ongoing improvements in PBL schemes focused on wind energy applications (Olson et al, 2011) will further enhance model skill in predicting winds at the altitudes relevant for wind-energy applications. Future evaluations of numerical weather predictions for ramp events can exploit recent developments in refined simulations including large-eddy simulation (Mirocha et al, 2011 andLiu et al, 2011) and data assimilation (Delle Monache et al, 2011).…”

Section: Resultsmentioning

confidence: 99%

Mesoscale Simulations of a Wind Ramping Event for Wind Energy Prediction

Rhodes¹,

Lundquist²

2011

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Ramping events, or rapid changes of wind speed and wind direction over a short period of time, present challenges to power grid operators in regions with significant penetrations of wind energy in the power grid portfolio. Improved predictions of wind power availability require adequate predictions of the timing of ramping events. For the ramping event investigated here, the Weather Research and Forecasting (WRF) model was run at three horizontal resolutions in "mesoscale" mode: 8100m, 2700m, and 900m. Two Planetary Boundary Layer (PBL) schemes, the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) schemes, were run at each resolution as well. Simulations were not "tuned" with nuanced choices of vertical resolution or tuning parameters so that these simulations may be considered "out-of-the-box" tests of a numerical weather prediction code. Simulations are compared with sodar observations during a wind ramping event at a "West Coast North America" wind farm. Despite differences in the boundary-layer schemes, no significant differences were observed in the abilities of the schemes to capture the timing of the ramping event. As collaborators have identified, the boundary conditions of these simulations probably dominate the physics of the simulations. We suggest that future investigations into characterization of ramping events employ ensembles of simulations, and that the ensembles include variations of boundary conditions. Furthermore, the failure of these simulations to capture not only the timing of the ramping event but the shape of the wind profile during the ramping event (regardless of its timing) indicates that the set-up and execution of such simulations for wind power forecasting requires skill and tuning of the simulations for a specific site.

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Section: Resultsmentioning

confidence: 99%

Mesoscale Simulations of a Wind Ramping Event for Wind Energy Prediction

Rhodes¹,

Lundquist²

2011

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“…Future work is needed to investigate the effects of higher resolution on forecasts for wind farms in complex terrain as the wind farm in this study is located in relatively simple topography. Our results suggest that future wind forecasting models of ramping events require "skilled" user expertise and should exploit recent developments in refined simulations including large-eddy simulation (see Mirocha et al 2011 andLiu et al 2011). The site location and seasonal timing of ramping events studied here might not have also fully showed the utility of a coupled subsurface-surface-atmosphere model.…”

Section: Recommendations and Future Workmentioning

confidence: 87%

Review of Wind Energy Forecasting Methods for Modeling Ramping Events

Wharton¹,

Lundquist²,

Marjanovic³

et al. 2011

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Executive Summary Relevance to the DOE Wind Power Program and wind industryTall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved.In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or "ramping events" at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument.Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.A brief look at the forecast models WRF mesoscale: In Chapter 2, the numerical Weather and Research Forecasting model (WRF) is applied to the wind park domain in mesoscale forecasting mode, with no perturbations made to the model physics. Here, WRF is considered the control run and is used to simulate an "out-of-thebox" version of WRF which requires minimal expertise from the user and minimal input about site conditions. Mesoscale WRF with "skilled" user input changes to horizontal and vertical resolution, nesting levels, and land surface conditions is applied in Chapter 3. WRF-LES:A novel application of large-eddy simulation (LES) to wind energy forecasting is examined in Chapter 3. WRF-LES is a high-resolution, turbulence-resolving mode of WRF. Here, WRF-LES is tested with two LES closure schemes: a turbulent kinetic energy closure of order 1.5 (TKE 1.5) and the Dynamic Reconstruction Model (DRM). PF.WRF:The influence of subsurface hydrology and hence, surface exchanges of heat and moisture on wind conditions is examined in Chapter 4. PF.WRF is a fully-coupled, groundwater-to-atmosphere model which incorporates the 3-D, variably-saturated hydrologic model ParFlow and WRF to simulate physics from bedrock to the top of the atmosphere. A brief look at the forecasted ramping eventsThe ramping events include times of rapid increases in wind speed during a synoptically-forced period in February (Case S), a ...

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“…It is referred to as the deterministic cluster, or XCEL-C1. For more information on the RTFDDA-WRF subsystem, please see [8].…”

Section: Real-time Four Dimensional Data Assimilation (Rtfdda)mentioning

confidence: 99%

“…Wind forecasting vendors have already developed sophisticated algorithms with limited real-time data. Further, Level 1 plants -especially thirdparties within the Balancing Authority (BA) -may provide real-time data to Xcel Energy in the future either per a recent FERC Notice of Proposed Rulemaking (NOPR) 8 or through other commercial agreements. Level 2 plants tend to be older plants with incompatible SCADA systems for the data collection process that, as they upgrade their systems, will become data-rich (Level 3).…”

Section: Level 1 and 2 Wind Plantsmentioning

confidence: 99%